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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
DOE OSTI2023

Inference of the optical depth to reionization τ from Planck CMB maps with convolutional neural networks

The optical depth to reionization, τ, is the least constrained parameter of the cosmological Λ cold dark matter (ΛCDM) model. To date, its most precise value is inferred from large-scale polarized cosmic microwave background (CMB) power spectra from the High Frequency Instrument (HFI) aboard the Planck satellite. These maps are known to contain significant contamination by residual non-Gaussian systematic effects, which are hard to model analytically. Therefore, robust constraints on τ are currently obtained through an empirical cross-spectrum likelihood built from simulations. In this paper, we present a likelihood-free inference of τ from polarized Planck HFI maps which, for the first time, is fully based on neural networks (NNs). NNs have the advantage of not requiring an analytical description of the data and can be trained on state-of-the-art simulations, combining the information from multiple channels. By using Gaussian sky simulations and Planck SRoll2 simulations, including CMB, noise, and residual instrumental systematic effects, we trained, tested, and validated NN models considering different setups. We inferred the value of τ directly from Stokes Q and U maps at ~4° pixel resolution, without computing angular power spectra. On Planck data, we obtained τ NN = 0.0579 ± 0.0082, which is compatible with current EE cross-spectrum results but with a ~30% larger uncertainty, which can be assigned to the inherent nonoptimality of our estimator and to the retraining procedure applied to avoid biases. While this paper does not improve on current cosmological constraints on τ, our analysis represents a first robust application of NN-based inference on real data, and highlights its potential as a promising tool for complementary analysis of near-future CMB experiments, also in view of the ongoing challenge to achieve the first detection of primordial gravitational waves.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Analysis and Application of Novel and Heritage Acceleration Limiting Algorithms for SLS on Ascent

National Aeronautics and Space Administration (NASA) is currently building the Space Launch System (SLS) Block-1 launch vehicle, to be used as the crewed heavy-lift vehicle for the Artemis series of missions. The SLS Block-1 guidance subsystem utilizes a nonlinear algorithm derived from Shuttle heritage for limiting the vehicle’s induced maximum axial acceleration during ascent flight, known as g-limiting. Even though g-limiting has demonstrated stability and robustness through several design analysis cycles and the extensive Shuttle flight history, there are no available documents that demonstrate that this algorithm has been proven stable through conventional controls stability analysis. This paper highlights the non-linear nature of g-limit, presents an alternative methodology to employ a linear version of this algorithm, performs assessment of selected linear gains using classical stability analysis and, conducts a comparison of both approaches through Six Degrees-of-Freedom (6-DOF) Monte Carlo (MC) simulations.

Jason Everett↗
DOE OSTI2025

Three-dimensional analysis of microbunched electron cooling

Microbunched electron cooling (MBEC, Ratner, ), a special category of coherent electron cooling, has been under consideration as a candidate method for the strong hadron cooling component of the Electron Ion Collider (EIC) at BNL. Most of the theoretical treatments of this scheme so far have been based on simplified models for the key space charge effect in which electrons and/or hadrons are approximated by charged disks. Although such disk-based models provide a flexible tool that captures a good part of the underlying physics, they lack the fidelity and robustness of a rigorous analysis that explicitly treats the hadron and cooler electron beams as collections of point charges. In this paper, we present such a rigorous, three-dimensional (3D) model, both from a theory-based and a simulation perspective. Specifically, we calculate the generalized wakefield (or Green’s function) of the cooling system—a crucial quantity that determines the overall performance—paying special attention to the dependence of the wake on the hadron transverse positions. Additionally, our treatment takes into account previously neglected 3D effects that can cause damping of the plasma oscillations in the amplification section of the cooler, such as focusing and the angular spread of the electron beam. Published by the American Physical Society 2025

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

TCF Base Technology-Specific: Real-time soil core scanner for carbon and other elements (Final Report)

The aim of this project was to commercialize an instrument that will accurately and precisely measure carbon in soil, providing a breakthrough in scalable soil core analysis and enabling a robust measurement of the total amount of carbon per acre. The instrument will measure the whole soil core, rather than just a few sub-samples, and provide data for carbon depth profiling, as well as other key soil elements such as Al, Si, O, Fe. This instrument will provide faster turnaround times and more precise results than current methods (such as loss on ignition), facilitating the analysis of many soil cores per acre. Ultimately, this will enable farmers to improve their carbon-in-soil content, thus contributing to an improved soil health and product yield. To achieve this goal, we divided the project into three main tasks: 1) commercialization research, 2) technical development, and 3) instrument development, demonstration, and benchmarking.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

A new class of tunable hypersonic phononic crystals based on polymer-tethered colloids

The design and engineering of hybrid materials exhibiting tailored phononic band gaps are fundamentally relevant to innovative material technologies in areas ranging from acoustics to thermo-optic devices. Phononic hybridization gaps, originating from the anti-crossing between local resonant and propagating modes, have attracted particular interest because of their relative robustness to structural disorder and the associated benefit to ‘manufacturability’. Although hybridization gap materials are well known, their economic fabrication and efficient control of the gap frequency have remained elusive because of the limited property variability and expensive fabrication methodologies. Here we report a new strategy to realize hybridization gap materials by harnessing the ‘anisotropic elasticity’ across the particle–polymer interface in densely polymer-tethered colloidal particles. Theoretical and Brillouin scattering analysis confirm both the robustness to disorder and the tunability of the resulting hybridization gap and provide guidelines for the economic synthesis of new materials with deliberately controlled gap position and width frequencies.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Tandem Mass Tag Labeling Facilitates Reversed-Phase Liquid Chromatography-Mass Spectrometry Analysis of Hydrophilic Phosphopeptides

Protein phosphorylation is a critical post-translational modification (PTM). Despite recent technological advances in reversed-phase liquid chromatography (RPLC)-mass spectrometry (MS)-based proteomics, comprehensive phosphoproteomic coverage in complex biological systems remains challenging, especially for hydrophilic phosphopeptides with enriched regions of serines, threonines, and tyrosines that often orchestrate critical biological functions. It is known that G protein coupled receptors (GPCRs) are regulators of cellular signaling events and rely on phosphorylation of serines and threonines within the GPCR C-terminus for appropriate signaling. However, the low abundance of GPCRs, combined with the hydrophilicity of C-terminal phosphopeptides, has prevented robust RPLC-MS analysis of potentially crucial regions. To address this issue, we developed a simple, easily implemented method to introduce a commonly used tandem mass tag (TMT) to increase peptide hydrophobicity, effectively enhancing RPLC-MS analysis of hydrophilic peptides. This method was applied to study the peptide QPSSSR, a tryptic peptide located on the C-terminus of the GPCR CXCR3 not been reported, and validated by comparative RPLC-MS analyses of both a hydrophilic QPSSSR peptide library as well as common phosphopeptides before and after TMT labeling. We further confirmed the utility of this method by quantifying QPSSSR phosphorylation abundances in HEK 293 cells under different treatement conditions predicted to alter QPSSSR phosphorylation. We anticipate that this simple TMT-labeling method can be broadly used not only for decoding GPCR phosphoproteomes, but also for effective RPLC-MS analysis of other highly hydrophilic analytes.

Tsai, Chia-Feng↗
DOE OSTI2024

Stochastic Optimization and Uncertainty Quantification of Natrium-based Nuclear-Renewable Energy Systems for Flexible Power Applications in Deregulated Markets

Rapid integration of variable renewable energy sources (VRES) has made modeling and stochastic optimization of hybrid energy systems crucial for studying their long-term performance and viability. However, most studies have focused on just historical data, which may be unreliable for capturing short-term fluctuations, rare events, and long-term patterns of energy demand, price, and the variability of renewable energy sources. For this study, optimal synthetic time series models were developed using Wasserstein distance. The models were validated by comparing the key statistical measures against those of the historical data. They were then used to optimize the integrated Natrium-style advanced energy systems and their long-term (30 years) economics. The stochastic model performs bi-level optimization to find the optimal sizes for the balance of plant and thermal energy storage, while also optimizing energy dispatch to achieve the maximum net present value. In studies of two deregulated markets (California ISO and the Electric Reliability Council of Texas), the integrated Natrium-style system performed better in CAISO than in ERCOT, given higher and more consistent electricity prices during peak-demand periods. The potentially enlarged cost associated with the variable operation and maintenance of the TES system also plays a significant role in driving the system sizing, thus its impacts on the system are investigated in detail through comparison against a baseline case. The study also finds that the bi-level optimization results based on stochastic gradient descent closely match the grid search results. The uncertainty quantification of the stochastic signals provides further NPV-related insights and probability distributions for the case studies. The normal standard error of the mean of NPV for the case with and without TES VOM for CAISO were found to be 7.73M (plus-minus sign) 1.09M USD and 104.99M (plus-minus sign) 1.25M USD, respectively based on a 95% confidence. Given the relatively small NPV variance based on 150 samples, the analysis affords the most robust possible prediction of the techno-economic performance of the integrated Natrium-style energy systems.

25 ENERGY STORAGE↗
NASA NTRS2006

An Overview of the Role of Systems Analysis in NASA's Hypersonics Project

NASA's Aeronautics Research Mission Directorate recently restructured its Vehicle Systems Program, refocusing it towards understanding the fundamental physics that govern flight in all speed regimes. Now called the Fundamental Aeronautics Program, it is comprised of four new projects, Subsonic Fixed Wing, Subsonic Rotary Wing, Supersonics, and Hypersonics. The Aeronautics Research Mission Directorate has charged the Hypersonics Project with having a basic understanding of all systems that travel at hypersonic speeds within the Earth's and other planets atmospheres. This includes both powered and unpowered systems, such as re-entry vehicles and vehicles powered by rocket or airbreathing propulsion that cruise in and accelerate through the atmosphere. The primary objective of the Hypersonics Project is to develop physics-based predictive tools that enable the design, analysis and optimization of such systems. The Hypersonics Project charges the systems analysis discipline team with providing it the decision-making information it needs to properly guide research and technology development. Credible, rapid, and robust multi-disciplinary system analysis processes and design tools are required in order to generate this information. To this end, the principal challenges for the systems analysis team are the introduction of high fidelity physics into the analysis process and integration into a design environment, quantification of design uncertainty through the use of probabilistic methods, reduction in design cycle time, and the development and implementation of robust processes and tools enabling a wide design space and associated technology assessment capability. This paper will discuss the roles and responsibilities of the systems analysis discipline team within the Hypersonics Project as well as the tools, methods, processes, and approach that the team will undertake in order to perform its project designated functions.

Robinson, Jeffrey S.↗
DOE OSTI2021

Shock-ramp analysis test problem

Quasi-isentropic (ramp) compression is now a well-established experimental method and so are the analysis techniques to give Lagrangian sound speed, pressure, and density along the sample material's isentrope. A shock followed by ramp compression is a natural extension to investigate, for example, shock melt and refreeze on compression, or isentropes of states off the Hugoniot or principal isentrope. In practice, graded-density impactors produce initial shocks, compression by shaped laser pulses may be unable to produce a smooth pressure increase from zero, and incidental perturbations on the drive pulse may also give rise to shocks, so robust shock-ramp analysis methods will be needed. Appropriate analysis methods are needed for shock-ramp experiments, based on those for quasi-isentropic compression, and these require validation. This paper describes three different analyses of a shock-ramp test problem, including an assessment of their estimated errors. The methods tested were based on hydrodynamic characteristics or integration backward in space. All methods gave the known Lagrangian sound speed to within ~1%, and pressure and volume to within less than 2% and 1%, demonstrating that the analysis methods of isentropic compression experiments can be confidently extended to the analysis of shock and ramp compression.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1991

Robustness of solutions to a benchmark control problem

The stochastic robustness of solutions to a benchmark control design problem has been analyzed. The analysis quantifies the controllers' stability and performance robustness with structured uncertainties in up to six system parameters. The analysis provides insights about system response that are not readily derived from other robustness criteria, providing a common ground for judging controllers produced by alternative methods.

Stengel, Robert F.↗
NASA NTRSDate not supplied

Simultaneous Development and Robust Optimization of a Microstructure Dependent Material

Recent microstructure characterization techniques combined with Symbolic Regression(SR)analysis has been proven to generate white box plasticity models well suited for incorporation into FEA software.The current work builds upon those efforts and demonstrates the applicability of Sequential Monte-Carlo (SMC) methods within SR analysis to condense model development and robust optimization into a single, co-dependent process. In this project, SMC methods provide a mechanism through which the observed microstructure features and associated variability can be incorporated into the discovery phase of model development and simultaneously recover approximate parameter distributions through SR analysis. The demonstration utilized a data set consisting of tensile test results from a limited number of sample specimens with corresponding EBSD data from which microstructure features were characterized.The maximum threshold stress model in the Visco-Plastic Self-Consistent (VPSC) code developed by Los Alamos National Laboratories was calibrated using mechanical test data.Synthetic volume elements with statistically equivalent microstructure were generated with DREAM3Dbased on the observed EBSD data. VPSC was used to simulate the corresponding tensile test response for each of the synthetic volume elements. The simulated microstructure and tensile test data was used astraining datafor SMC-SR algorithm and the resulting model was validated with data from the original empirical data set.

Karl Garbrecht↗
DOE OSTI2020

Simulation of the Charge Measurements for the SuperCDMS Soudan Experiment

Astronomical observations lead us to believe that dark matter constitutes the majority of the mass of the Universe, yet it has never been directly observed experimentally. The Super Cryogenic Dark Matter Search Experiment (SuperCDMS) aims to discover the particle nature of dark matter, by developing and using some of the most sensitive detectors ever built. The SuperCDMS detectors are capable of rejecting known particles to search for dark matter interactions, but the discrimination is a complicated analysis task. Previous analyses with SuperCDMS set world leading sensitivity limits to dark matter interactions, but the analysis techniques have not been based on simulations. Now we have developed an efficient simulations infrastructure that will help better understand the detectors, develop a better background model, and optimize the next generation dark matter searches. In this thesis we present the fully-functional simulations infrastructure to produce high quality samples a s well as results for the charge system readout simulations, and comparisons to expectations from data. We show that our simulations well-reproduce dominant features of data, bringing SuperCDMS closer to a robust simulation-based analysis method, much needed for the upcoming SuperCDMS dark matter searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2009

Data Analysis for the LISA Pathfinder Mission

The LTP (LISA Technology Package) is the core part of the Laser Interferometer Space Antenna (LISA) Pathfinder mission. The main goal of the mission is to study the sources of any disturbances that perturb the motion of the freely-falling test masses from their geodesic trajectories as well as 10 test various technologies needed for LISA. The LTP experiment is designed as a sequence of experimental runs in which the performance of the instrument is studied and characterized under different operating conditions. In order to best optimize subsequent experimental runs, each run must be promptly analysed to ensure that the following ones make best use of the available knowledge of the instrument ' In order to do this, all analyses must be designed and tested in advance of the mission and have sufficient built-in flexibility to account for unexpected results or behaviour. To support this activity, a robust and flexible data analysis software package is also required. This poster presents two of the main components that make up the data analysis effort: the data analysis software and the mock-data challenges used to validate analysis procedures and experiment designs.

Thorpe, James Ira↗
DOE OSTI2026

Adaptively coupled phase retrieval in multi-peak Bragg coherent diffraction imaging

Recent advances in Bragg coherent diffraction imaging (BCDI) experimental techniques permit routine measurement of multiple Bragg peaks from a single crystalline grain. The resulting images contain the full lattice distortion vector field which can be differentiated to provide lattice strain and rotation. With the advent of fourth-generation synchrotron light sources, such multi-peak datasets are produced at high rates, facilitating the need for rapid phase retrieval of the multiple peaks and subsequent image analysis. Here we describe and demonstrate a new implementation of a coupled phase retrieval technique for multi-peak BCDI which simultaneously treats each Bragg peak of the dataset and produces a three-dimensional image of the crystal's morphology and lattice distortion field. In addition, this method uses the redundant information contained in the various Bragg diffraction patterns to detect and suppress spurious signal appearing on the detector in a subset of the measurements. Compared with manual data editing, adaptive coupling produces a more consistent phase profile in reciprocal space and sharper surfaces in direct space, with no significant difference in computational cost. These improvements reduce the need for manual preprocessing and enable robust high-throughput analysis of multi-peak BCDI data, supporting near-real-time strain microscopy at modern synchrotron facilities.

36 MATERIALS SCIENCE↗
DOE OSTI2018

GenomeTrakr proficiency testing for foodborne pathogen surveillance: an exercise from 2015

Pathogen monitoring is becoming more precise as sequencing technologies become more affordable and accessible worldwide. This transition is especially apparent in the field of food safety, which has demonstrated how whole-genome sequencing (WGS) can be used on a global scale to protect public health. GenomeTrakr coordinates the WGS performed by public-health agencies and other partners by providing a public database with real-time cluster analysis for foodborne pathogen surveillance. Because WGS is being used to support enforcement decisions, it is essential to have confidence in the quality of the data being used and the downstream data analyses that guide these decisions. Routine proficiency tests, such as the one described here, have an important role in ensuring the validity of both data and procedures. In 2015, the GenomeTrakr proficiency test distributed eight isolates of common foodborne pathogens to participating laboratories, who were required to follow a specific protocol for performing WGS. Resulting sequence data were evaluated for several metrics, including proper labelling, sequence quality and new single nucleotide polymorphisms (SNPs). Illumina MiSeq sequence data collected for the same set of strains across 21 different laboratories exhibited high reproducibility, while revealing a narrow range of technical and biological variance. The numbers of SNPs reported for sequencing runs of the same isolates across multiple laboratories support the robustness of our cluster analysis pipeline in that each individual isolate cultured and resequenced multiple times in multiple places are all easily identifiable as originating from the same source.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 μs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Dark energy survey year 3 results: cosmology from galaxy clustering and galaxy–galaxy lensing in harmonic space

We present the joint tomographic analysis of galaxy-galaxy lensing and galaxy clustering in harmonic space (HS), using galaxy catalogues from the first three years of observations by the Dark Energy Survey (DES Y3). We utilize the redMaGiC and MagLim catalogues as lens galaxies and the metacalibration catalogue as source galaxies. The measurements of angular power spectra are performed using the pseudo-$C_\ell$ method, and our theoretical modelling follows the fiducial analyses performed by DES Y3 in configuration space, accounting for galaxy bias, intrinsic alignments, magnification bias, shear magnification bias and photometric redshift uncertainties. We explore different approaches for scale cuts based on non-linear galaxy bias and baryonic effects contamination. Our fiducial covariance matrix is computed analytically, accounting for mask geometry in the Gaussian term, and including non-Gaussian contributions and super-sample covariance terms. To validate our HS pipelines and covariance matrix, we used a suite of 1800 log-normal simulations. We also perform a series of stress tests to gauge the robustness of our HS analysis. In the $\Lambda$CDM model, the clustering amplitude $S_8 =\sigma _8(\Omega _m/0.3)^{0.5}$ is constrained to $S_8 = 0.704\pm 0.029$ and $S_8 = 0.753\pm 0.024$ (68 per cent C.L.) for the redMaGiC and MagLim catalogues, respectively. For the wCDM, the dark energy equation of state is constrained to $w = -1.28 \pm 0.29$ and $w = -1.26^{+0.34}_{-0.27}$, for redMaGiC and MagLim catalogues, respectively. These results are compatible with the corresponding DES Y3 results in configuration space and pave the way for HS analyses using the DES Y6 data.

(cosmology:) cosmological parameters↗